Search

Alzheimer’s disease (AD) is a neurodegenerative disorder caused by a variety of factors, including age, genetic susceptibility, cardiovascular disease, traumatic brain injury, and environmental factors. The pathogenesis of AD is largely associated with the overproduction and accumulation of amyloid-β peptides and the hyperphosphorylation of tau protein in the brain. Recent studies have identified the presence of diverse pathogens, including viruses, bacteria, and parasites, in the tissues of AD patients, underscoring the critical role of central nervous system infections in inducing pathological changes associated with AD. Nevertheless, it remains unestablished about the specific mechanism by which infections lead to the occurrence of AD. As an important post-transcriptional RNA modification, RNA 5-methylcytosine (m5C) methylation regulates a wide range of biological processes, including RNA splicing, nuclear export, stability, and translation, therefore affecting cellular function. Moreover, it has been recently demonstrated that multiple pathogenic microbial infections are associated with the m5C methylation of the host. However, the role of m5C methylation in infectious AD is still uncertain. Therefore, this review discusses the mechanisms of pathogen-induced AD and summarizes research on the molecular mechanisms of m5C methylation in infectious AD, thereby providing new insight into exploring the mechanism underlying infectious AD.

Abstract Cigarette smoke (CS) has been generally recognized as a chief carcinogenic factor in renal cell carcinoma (RCC). The stimulative effect of CS on renal cancer stem cells (RCSCs) has been described previously. The Sonic Hedgehog (SHH) pathway plays an essential role in self-renewal, cell growth, drug resistance, metastasis, and recurrence of cancer stem cells (CSCs). Renal cancer-related gene ΔNp63α is highly expressed in renal epithelial tissues and contributes to the RCSCs characteristics of tumors. The aim of this study was to elucidate the role of ΔNp63α and the SHH pathway on the activity of RCSCs induced by CS through a series of in vivo and in vitro studies. It was shown that in renal cancer tissues, ΔNp63α and RCSCs markers in smokers are expressed higher than that in non-smokers. RCSCs were effectively enriched by tumor sphere formation assay. Besides, CS increased the expression of RCSCs markers and the capability of sphere-forming in vitro and in vivo. Moreover, the SHH pathway was activated, and the specialized inhibitor alleviated the promotion of CS on RCSCs. ΔNp63α activated the SHH pathway and promoted CS-induced enhancement of RCSCs activity. These findings indicate that ΔNp63α positively regulates the activity of CS-induced RCSCs via the SHH pathway.

Abstract Threatening public health, pulmonary disease (PD) encompasses diverse lung injuries like chronic obstructive PD, pulmonary fibrosis, asthma, pulmonary infections due to pathogen invasion, and fatal lung cancer. The crucial involvement of RNA epigenetic modifications in PD pathogenesis is underscored by robust evidence. These modifications not only shape cell fates but also finely modulate the expression of genes linked to disease progression, suggesting their utility as biomarkers and targets for therapeutic strategies. The critical RNA modifications implicated in PDs are summarized in this review, including N6‐methylation of adenosine, N1‐methylation of adenosine, 5‐methylcytosine, pseudouridine (5‐ribosyl uracil), 7‐methylguanosine, and adenosine to inosine editing, along with relevant regulatory mechanisms. By shedding light on the pathology of PDs, these summaries could spur the identification of new biomarkers and therapeutic strategies, ultimately paving the way for early PD diagnosis and treatment innovation.

Abstract The specific energy of Li metal batteries (LMBs) can be improved by using high‐voltage cathode materials; however, achieving long‐term stable cycling performance in the corresponding system is particularly challenging for the liquid electrolyte. Herein, a novel pseudo‐oversaturated electrolyte (POSE) is prepared by introducing 1,1,2,2‐tetrafluoroethyl‐2,2,3,3‐tetrafluoropropyl ether (TTE) to adjust the coordination structure between diglyme (G2) and lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). Surprisingly, although TTE shows little solubility to LiTFSI, the molar ratio between LiTFSI and G2 in the POSE can be increased to 1:1, which is much higher than that of the saturation state, 1:2.8. Simulation and experimental results prove that TTE promotes closer contact of the G2 molecular with Li+ in the POSE. Moreover, it also participates in the formation of electrolyte/electrode interphases. The electrolyte shows outstanding compatibility with both the Li metal anode and typical high‐voltage cathodes. Li||Li symmetric cells show a long life of more than 2000 h at 1 mA cm−2, 1 mAh cm−2. In the meantime, Li||LiNi0.8Co0.1Mn0.1O2 (NCM811) cell with the POSE shows a high reversible capacity of 134.8 mAh g−1 after 900 cycles at 4.5 V, 1 C rate. The concept of POSE can provide new insight into the Li+ solvation structure and in the design of advanced electrolytes for LMBs.

The Corona Virus Disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has quickly spread worldwide and resulted in significant morbidity and mortality. Although most infections are mild, some patients can also develop severe and fatal myocarditis. In eukaryotic RNAs, 5-methylcytosine (m5C) is a common kind of post-transcriptional modification, which is involved in regulating various biological processes (such as RNA export, translation, and stability maintenance). With the rapid development of m5C modification detection technology, studies related to viral m5C modification are ever-increasing. These studies have revealed that m5C modification plays an important role in various stages of viral replication, including transcription and translation. According to recent studies, m5C methylation modification can regulate SARS-CoV-2 infection by modulating innate immune signaling pathways. However, the specific role of m5C modification in SARS-CoV-2-induced myocarditis remains unclear. Therefore, this review aims to provide insights into the molecular mechanisms of m5C methylation in SARS-CoV-2 infection. Moreover, the regulatory role of NSUN2 in viral infection and host innate immune response was also highlighted. This review may provide new directions for developing therapeutic strategies for SARS-CoV-2-associated myocarditis.

This study aimed to create a robust prediction model for sepsis patient mortality and identify key biomarkers in those with myocardial injury. A retrospective analysis of 261 sepsis inpatients was conducted, with 44 deaths and 217 recoveries. Key factors were assessed via univariate and multivariate analyses, revealing myocardial injury, shock, and pulmonary infection as independent mortality risk factors. Using LASSO regression, a reliable prediction model was developed and internally validated. Additionally, procalcitonin (PCT) emerged as a sensitive biomarker for myocardial injury prediction in sepsis patients. In summary, this study highlights myocardial injury, shock, and pulmonary infection as independent risk factors for sepsis-related deaths. The LASSO-based prediction model effectively forecasts the prognosis of septic patients with myocardial injury, with PCT showing promise as a predictive biomarker.

Abstract Since its discovery in 2019, coronavirus disease 2019 (COVID-2019) spans a wide clinical spectrum from the asymptomatic stage, mild infection, to severe pneumonia. In patients with COVID-2019, factors such as advanced age, diabetes, or hypertension are associated with a significantly increased risk of severe diseases and death. Of note, the mechanisms underlying differences in the risk and symptoms of COVID-2019 among different populations are still poorly characterized. Accordingly, it is imperative to elucidate potential pathophysiological mechanisms and develop targeted therapeutic approaches for COVID-2019 infection. N6-methyladenosine (m6A) is one of the most common modifications in mammalian RNA transcripts and is widely found in messenger RNAs and some non-coding RNAs. It has been reported that m6A methylation modifications are present in viral RNA transcripts, which are of great significance for the regulation of the viral life cycle. Furthermore, m6A methylation has recently been found to be strongly associated with COVID-2019 infection. Therefore, this article reviews recent advances in studies related to the role of m6A methylation in COVID-2019 infection.

Abstract Background This study aims to deeply explore the relationship between m6A methylation modification and peripheral immune cells in patients with advanced sepsis and mine potential epigenetic therapeutic targets by analyzing the differential expression patterns of m6A-related genes in healthy subjects and advanced sepsis patients. Methods A single cell expression dataset of peripheral immune cells containing blood samples from 4 patients with advanced sepsis and 5 healthy subjects was obtained from the gene expression comprehensive database (GSE175453). Differential expression analysis and cluster analysis were performed on 21 m6A-related genes. The characteristic gene was identified based on random forest algorithm, and the correlation between the characteristic gene METTL16 and 23 immune cells in patients with advanced sepsis was evaluated using single-sample gene set enrichment analysis. Results IGFBP1, IGFBP2, IGF2BP1, and WTAP were highly expressed in patients with advanced sepsis and m6A cluster B. IGFBP1, IGFBP2, and IGF2BP1 were positively correlated with Th17 helper T cells. The characteristic gene METTL16 exhibited a significant positive correlation with the proportion of various immune cells. Conclusion IGFBP1, IGFBP2, IGF2BP1, WTAP, and METTL16 may accelerate the development of advanced sepsis by regulating m6A methylation modification and promoting immune cell infiltration. The discovery of these characteristic genes related to advanced sepsis provides potential therapeutic targets for the diagnosis and treatment of sepsis.

Previously, it was believed that type III interferon (IFN-III) has functions similar to those of type I interferon (IFN-I). However, recently, emerging findings have increasingly indicated the non-redundant role of IFN-III in innate antiviral immune responses. Still, the regulatory activity of IFN-III in adaptive immune response has not been clearly reported yet due to the low expression of IFN-III receptors on most immune cells. In the present study, we reviewed the adjuvant, antiviral, antitumor, and disease-moderating activities of IFN-III in adaptive immunity; moreover, we further elucidated the mechanisms of IFN-III in mediating the adaptive antiviral immune response in a thymic stromal lymphopoietin (TSLP)-dependent manner, a pleiotropic cytokine involved in mucosal adaptive immunity. Research has shown that IFN-III can enhance the antiviral immunogenic response in mouse species by activating germinal center B (GC B) cell responses after stimulating TSLP production by microfold (M) cells, while in human species, TSLP exerts OX40L for regulating GC B cell immune responses, which may also depend on IFN-III. In conclusion, our review highlights the unique role of the IFN-III/TSLP axis in mediating host adaptive immunity, which is mechanically different from IFN-I. Therefore, the IFN-III/TSLP axis may provide novel insights for clinical immunotherapy.

Bromadiolone, as a second-generation coumarin anticoagulant rodenticide, may accidently cause harm to humans and non-target animals when overused or misused due to its high toxicity and long-lasting effects. In some severe cases such as the presence of active bleeding, treatment should involve the administration of hemoperfusion therapy. Nafamostat mesylate is a synthesized protease inhibitor that inhibits most factors in the coagulation process, preventing clotting and ensuring smooth blood flow during the procedure. Nafamostat mesylate helps maintain the efficacy and safety of hemoperfusion treatment. Despite its wide application in Japan, the clinical practice and research of nafamostat mesylate are limited in China, especially for patients undergoing maintenance hemodialysis. This paper reports two cases of bromadiolone poisoning and describes the treatment procedure and therapeutic effect of anticoagulation in hemoperfusion therapy with nafamostat mesylate.

Age-related hearing loss (ARHL) is a common issue associated with aging. One of the typical causes of hearing loss is the damage to inner ear hair cells. In addition, oxidative stress and inflammation contribute to ARHL. To avoid excessive inflammatory responses, non-classical scorch death pathway by cell membrane lipopolysaccharide (LPS) activates of caspase-11. Piceatannol (PCT) is also known for anti-tumor, antioxidant and anti-inflammatory effects; however, the protective effect of piceatannol (PCT) on ARHL is unclear. The aim of this study was to elucidate the mechanism underlying protective effect of PCT on ARHL-induced inner ear hair cell damage. In vivo experiments showed that PCT could protect mice from inflammatory aging-induced hearing loss as well as from inner hair cells (IHC) and spiral ganglion (SG) deficits. In addition, inflammatory vesicle inhibitor BAY11–7082 ameliorated ARHL, inhibited NLRP3 and reduced GSDMD expression. In in vitro experiments we used LPS and D-gal to simulate the aging inflammatory environment. The results showed that intracellular reactive oxygen species levels, expression of Caspase-11, NLRP3, and GSDMD were significantly increased, yet treatment with PCT or BAY11–7082 significantly improved HEI-OC-1 cell injury while reducing inflammation-associated protein expression as well as the occurrence of pyroptosis. In conclusion, these results suggest a protective role for PCT against ARHL, possibly through Caspase-11-GSDMD pathway. Our findings may provide a new target and theoretical basis for hearing loss treatment using PCT.

Objective Osteoarthritis (OA) is characterized by synovial cartilage degeneration and is the leading cause of disability and pain worldwide. This study sought to investigate the expression of integrin beta-2 (ITGB2) in synovial fluid of OA patients and its clinical significance. Methods A total of 110 OA patients were enrolled, who were classified into grade I ( N = 35), II ( N = 42), and III ( N = 33) according to the Kellgren-Lawrence classification, with 110 healthy subjects as controls, and their clinical data were compared. ITGB2 level was detected by RT-qPCR. The receiver operating characteristic curve was used to analyze the predictive value of ITGB2 on OA occurrence. The correlation between ITGB2 and bone metabolism indexes procollagen type I N-terminal peptide (PINP), bone glaprotein (BGP), bone alkaline phosphatase (BALP), and β-collagen I telopeptide (β-CTX) was analyzed by the Pearson method. Logistic regression model was performed to analyze the influencing factors of OA. Results The content of red blood cells, white blood cells, PINP, BGP, and BALP was lowered in OA patients, while β-CTX was elevated. ITGB2 was highly-expressed in OA patients, negatively-correlated with PINP, BGP, and BALP, but positively-correlated with β-CTX. ITGB2 level increased with the elevation of OA grade. The ITGB2 level >1.375 had certain diagnostic values for OA. ITGB2 level is related to OA severity and may be a biomarker for OA classification. ITGB2 was an independent risk factor for OA. Conclusion High expression of ITGB2 in synovial fluid can assist OA diagnosis and may be a biomarker for OA grade.

In the present study, the mechanism of electromagnetic resonance interference on an inductive speed sensor is investigated. To this end, a second-order equivalent resonance model is established based on the lumped parameter of the speed sensor. Then the effects of different parameters on the interference signal are analyzed. The effect of terminal loads and filter capacitances are simulated in the CST software and the obtained results for the resonance interference signal are analyzed. Moreover, an experiment is carried out and the oscillation of the voltage interference signal is produced by the speed sensor under the testing of early-time high altitude nuclear electromagnetic pulse (HEMP) field. The GTEM cell is used to produce the plane wave for the experiment. Finally, the advantages and disadvantages of different resonance elimination methods are analyzed, and the method is proposed to eliminate the oscillation of the voltage interference signal.

Abstract Objectives To share our initial experience with the modified vein clamping technique for the treatment of renal cell carcinoma complicated with level I–II IVC thrombi. Methods From March 2018 to April 2021, 11 patients with renal cell carcinoma (RCC) involving an IVC tumour thrombus were admitted to our hospital. They all underwent laparoscopic radical nephrectomy and IVC thrombectomy (LRN-IVCTE) using a modified vein clamping technique. Results All procedures were successfully completed without conversion to open surgery. The median operative time was 185.00 min (145.00–216.00 min); the median estimated blood loss was 200.00 ml (155.00–300.00 ml), and four patients received an intraoperative transfusion. In addition, the median IVC clamping time was 18.00 min (12.00–20.00 min); the median postoperative hospital stay was 6.00 days (4.00–7.00 days), while the median follow-up period was 28.00 months (4.00–34.00 months). Conclusions The modified vein clamping technique for the treatment of renal cell carcinoma complicated with level I–II IVC thrombi may be a safe and technically feasible alternative technique.

Abstract Background Cervical cancer (CC) endangers women’s health in the world range. Accumulating studies have revealed the crucial regulatory role of long non-coding RNAs (lncRNAs) in multiple malignancies, including CC. Our study aimed to explore the role of lncRNA double homeobox A pseudogene 8 (DUXAP8) in cervical carcinogenesis. Methods Gene expressions in CC were assessed by RT-qPCR. Function experiments and tube formation assays were performed to evaluate the role of DUXAP8 in CC cells. Subcellular fractionation and FISH assays were conducted to determine the subcellular location of DUXAP8. Luciferase reporter, RNA pull down and RIP assays were conducted to investigate the mechanism of DUXAP8. Results DUXAP8 was notably upregulated in CC cells. Downregulation of DUXAP8 repressed cell malignant behaviors and angiogenesis in CC. Mechanically, DUXAP8 boosted the expression of reticulocalbin-2 (RCN2) through relieving the binding of miR-1297 to RCN2 3’-UTR. Moreover, miR-1297 inhibition and RCN2 overexpression could counteract the inhibitory effects of DUXAP8 knockdown on the malignant phenotypes of CC cells. Besides, enhanced RCN2 expression restored the tumor growth in vivo that was inhibited by DUXAP8 repression. Conclusions DUXAP8 promotes malignant behaviors in CC cells via regulating miR-1297/RCN2 axis. Graphical Abstract

IntroductionSepsis is a severe clinical syndrome caused by dysregulated systemic inflammatory responses to infection. Methylation modification, as a crucial mechanism of RNA functional modification, can manipulate the immunophenotype and functional activity of immune cells to participate in sepsis progression. This study aims to explore the mechanism of N6-methyladenosine (m6A) methylation modification in immune cell-mediated sepsis through keyword search.MethodsLiterature retrieval.Results and DiscussionLiterature retrieval reveals that m6A methylation is implicated in sepsis-induced lung injury and myocardial injury,as well as sepsis-related encephalopathy. Furthermore, it is found that m6A methylation can regulate sepsis by inhibiting the chemotaxis of neutrophils and the formation of neutrophil extracellular traps and suppressing macrophage phagocytosis, thereby playing a role in sepsis.

Effective data-driven rotating machine fault diagnosis has recently been a research topic in the diagnosis and health management of machinery systems owing to the benefits, including safety guarantee, labor saving, and reliability improvement. However, in vast real-world applications, the classifier trained on one dataset will be extended to datasets under variant working conditions. Meanwhile, the deviation between datasets can be triggered easily by rotating speed oscillation and load variation, and it will highly degenerate the performance of machine learning-based fault diagnosis methods. Hence, a novel dataset distribution discrepancy measuring algorithm called high-order Kullback-Leibler (HKL) divergence is proposed. Based on HKL divergence and transfer learning, a new fault diagnosis network which is robust to working condition variation is constructed in this paper. In feature extraction, sparse filtering with HKL divergence is proposed to learn sharing and discriminative features of the source and target domains. In feature classification, HKL divergence is introduced into softmax regression to link the domain adaptation with health conditions. Its effectiveness is verified by experiments on a rolling bearing dataset and a gearbox dataset, which include 18 transfer learning cases. Furthermore, the asymmetrical performance phenomenon found in experiments is also analyzed.

Abstract Background CCL2 was up-regulated in neurons and involved in microglia activation and neurological decline in mice suffering from hepatic encephalopathy (HE). However, no data exist concerning the effect of neuron-derived CCL2 on microglia activation in vitro. Methods The rats were pretreated with CCL2 receptor inhibitors (INCB or C021, 1 mg/kg/day i.p.) for 3 days prior to thioacetamide (TAA) administration (300 mg/kg/day i.p.) for inducing HE model. At 8 h following the last injection (and every 4 h after), the grade of encephalopathy was assessed. Blood and whole brains were collected at coma for measuring CCL2 and Iba1 expression. In vitro, primary neurons were stimulated with TNF-α, and then the medium were collected for addition to microglia cultures with or without INCB or C021 pretreatment. The effect of the medium on microglia proliferation and activation was evaluated after 24 h. Results CCL2 expression and microglia activation were elevated in the cerebral cortex of rats received TAA alone. CCL2 receptors inhibition improved neurological score and reduced cortical microglia activation. In vitro, TNF-α treatment induced CCL2 release by neurons. Medium from TNF-α stimulated neurons caused microglia proliferation and M1 markers expression, including iNOS, COX2, IL-6 and IL-1β, which could be suppressed by INCB or C021 pretreatment. The medium could also facilitate p65 nuclear translocation and IκBα phosphorylation, and NF-κB inhibition reduced the increased IL-6 and IL-1β expression induced by the medium. Conclusion Neuron-derived CCL2 contributed to microglia activation and neurological decline in HE. Blocking CCL2 or inhibiting microglia excessive activation may be potential strategies for HE.

Case-based intelligent fault diagnosis methods of rotating machinery can deal with new faults effectively by adding them into the case library. However, case-based methods scarcely refer to automatic feature extraction, and k-nearest neighbor (KNN) commonly required by case-based methods is unable to determine the nearest neighbors for different testing samples adaptively. To solve these problems, a new intelligent fault diagnosis method of rotating machinery is proposed based on enhanced KNN (EKNN), which can take advantage of both parameter-based and case-based methods. First, EKNN is embedded with a dimension-reduction stage, which extracts the discriminative features of samples via sparse filtering (SF). Second, to locate the nearest neighbors for various testing samples adaptively, a case-based reconstruction algorithm is designed to obtain the correlation vectors between training samples and testing samples. Finally, according to the optimized correlation vector of each testing sample, its nearest neighbors can be adaptively selected to obtain its corresponding health condition label. Extensive experiments on vibration signal datasets of bearings are also conducted to verify the effectiveness of the proposed method.

The intensity data recorded by a terrestrial laser scanner (TLS) contain spectral characteristics of a scanned target and are mainly influenced by incidence angle and distance. In this study, an improved implementable method is proposed to empirically correct the intensity data of long-distance TLSs. Similar to existing methods, the incidence angle⁻intensity relationship is estimated using some reference targets scanned in the laboratory. By contrast, due to the length limit of indoor environments and the laborious data processing, the distance⁻intensity relationship is derived by selecting some natural homogeneous targets with distances covering the entire distance scale of the adopted long-distance TLS. A case study of intensity correction and point cloud classification in an intertidal zone in Chongming Island, Shanghai, China, is conducted to validate the feasibility of the improved method by using the intensity data of a long-distance TLS (Riegl VZ-4000). Results indicate that the improved method can accurately eliminate the effects of incidence angle and distance on the intensity data of long-distance TLSs; the coefficient of variation of the intensity data for the targets in the study intertidal zone can be reduced by approximately 54%. The classification results of the study intertidal zone show that the improved method can effectively eliminate the variations caused by the incidence angle and distance in the original intensity data of the same target to obtain a corrected intensity that merely depends on target characteristics for improving classification accuracy by 49%.

Faults in bearings and gearboxes, which are widely used in rotating machines, can lead to heavy investment and productivity loss. Accordingly, a fault diagnosis system is necessary to ensure a high-performance transmission. However, as mechanical fault diagnosis enters the era of big data, it can be difficult to apply traditional fault diagnosis methods because of the massive computation cost and excessive reliance on human labor. Meanwhile, unsupervised learning has been shown to have excellent performance in processing machanical big data. In this paper, an unsupervised learning method known as sparse filtering is applied, the multi-correlation of a weight matrix is investigated, and a method that is more suitable for the feature extraction of signals is proposed. The main contribution of our work is the modification of original method. First, to understand the non-monotonicity testing accuracies of the original method, the physical interpretation of input dimensions is studied. Second, using the physical interpretation, an overfitting phenomenon is discovered and examined. Third, to reduce the overfitting phenomenon, a method which eliminates the multi-correlation of the weight matrix is proposed. Finally, bearing and gear datasets are employed to verify the effectiveness of the proposed method; experimental results show that the proposed method can achieve a superior performance in comparison to the original sparse filtering model.

Alzheimer's disease (AD) is a neurodegenerative disorder caused by a variety of factors, including age, genetic susceptibility, cardiovascular disease, traumatic brain injury, and environmental factors. The pathogenesis of AD is largely associated with the overproduction and accumulation of amyloid-β peptides and the hyperphosphorylation of tau protein in the brain. Recent studies have identified the presence of diverse pathogens, including viruses, bacteria, and parasites, in the tissues of AD patients, underscoring the critical role of central nervous system infections in inducing pathological changes associated with AD. Nevertheless, it remains unestablished about the specific mechanism by which infections lead to the occurrence of AD. As an important post-transcriptional RNA modification, RNA 5-methylcytosine (m5C) methylation regulates a wide range of biological processes, including RNA splicing, nuclear export, stability, and translation, therefore affecting cellular function. Moreover, it has been recently demonstrated that multiple pathogenic microbial infections are associated with the m5C methylation of the host. However, the role of m5C methylation in infectious AD is still uncertain. Therefore, this review discusses the mechanisms of pathogen-induced AD and summarizes research on the molecular mechanisms of m5C methylation in infectious AD, thereby providing new insight into exploring the mechanism underlying infectious AD. [ABSTRACT FROM AUTHOR]

The Corona Virus Disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), has quickly spread worldwide and resulted in significant morbidity and mortality. Although most infections are mild, some patients can also develop severe and fatal myocarditis. In eukaryotic RNAs, 5-methylcytosine (m5C) is a common kind of post-transcriptional modification, which is involved in regulating various biological processes (such as RNA export, translation, and stability maintenance). With the rapid development of m5C modification detection technology, studies related to viral m5C modification are ever-increasing. These studies have revealed that m5C modification plays an important role in various stages of viral replication, including transcription and translation. According to recent studies, m5C methylation modification can regulate SARS-CoV-2 infection by modulating innate immune signaling pathways. However, the specific role of m5C modification in SARS-CoV-2-induced myocarditis remains unclear. Therefore, this review aims to provide insights into the molecular mechanisms of m5C methylation in SARS-CoV-2 infection. Moreover, the regulatory role of NSUN2 in viral infection and host innate immune response was also highlighted. This review may provide new directions for developing therapeutic strategies for SARS-CoV-2-associated myocarditis. [ABSTRACT FROM AUTHOR]